海耶斯和阿伯內(nèi)西，1980;海斯和加文,1982;卡普蘭，1986;缺乏戰(zhàn)略重點(diǎn)(斯金納,1974),促進(jìn)局部?jī)?yōu)化(哈勒,1983;弗萊和考克斯，1989),促進(jìn)方差最小化,而不是持續(xù)改進(jìn)(約翰遜和卡普蘭,1987;蘭什和克羅斯，1991),摧毀了制造業(yè)的競(jìng)爭(zhēng)力(海耶斯和阿伯內(nèi)西，1980),通常抑制創(chuàng)新(理查森和戈登,1980),而不是外部集中(卡普蘭和諾頓,1992)。

This research started by reviewing the traditional corporate performance measures which are mainly financial in nature and were mainly derived from costing and accounting systems (McAdam & Bannister 2001). These traditional performance measures were criticized for their historical nature (Dixon et al., 1990), providing little indication of future performance (Kennerley and Neely, 2003), encouraging short-termism (Banks and Wheelwright, 1979;

Hayes and Abernathy, 1980; Hayes and Garvin, 1982; Kaplan, 1986), lacking strategic focus (Skinner, 1974), promoting local optimization (Hall, 1983; Fry and Cox 1989), promoting minimization of variance rather than continuous improvement (Johnson and Kaplan, 1987; Lynch and Cross, 1991), destroying the competitiveness of manufacturing industry (Hayes and Abernathy, 1980), often inhibit innovation (Richardson and Gordon, 1980), and not being externally focused (Kaplan and Norton, 1992).

To counter some of these criticisms, researchers in field of performance measurement had tried to combine these financial measures with qualitative tools such as quality standards and management audit, operational reviews, comprehensive audit etc. (Sherman and Zhu, 2005).

Chapter two of this study reviews the field of business performance measurement by looking at the past researches in this field. The main objectives of this systematic literature survey was to review conceptual bases for performance measurement, practicalities and challenges, enduring questions and issues, evaluate existing performance measurement frameworks and methodologies and identify the key characteristics that they exhibit. Based on conceptual understanding, theoretical foundations, strengths and weakness of existing frameworks a new performance measurement framework has been proposed – that incorporates the best of the existing frameworks and methodologies. This comprehensive performance measurement framework is more holistic as it incorporates measurements to address multiple stakeholders, their satisfaction and includes contributions from leading thinkers around the world and recent developments in the theory & practice of performance measurement.

First section of this systematic review highlights the definitional and conceptual framework for performance measurement. It includes answers to the fundamental questions of performance measurement such as what performance means; what a performance measure is; what performance measurement is; and what a performance measurement framework is. Second section of this chapter reviews the why aspect of performance measurement i.e. why performance measurement is important in an organization.#p#分頁(yè)標(biāo)題#e#

The third section of the chapter reviews the how to measure aspect of the performance measurement i.e. performance measurement frameworks and methodologies. In this section, I have classified various performance measurement frameworks in to four categories. In first category i.e. accounting based financial performance measurement frameworks includes Dupont pyramid of financial ratios and Stern, Stewart & Company’s economic value addition EVA®. Second category i.e. financial & operational performance measurement frameworks include Keegan et al.’s (1989) supportive performance measures matrix, the SMART pyramid (Cross and Lynch, 1988/89), and the Results/Determinants Matrix (Fitzgerald and Moon, 1996; Fitzgerald, 1991). Third category i.e. performance measurement frameworks using Freeman’s stakeholder approach include the Balanced Scorecard (Kaplan and Norton, 1992), Performance Prism (Neely et al., 2002); Business Excellence Model of European Foundation for Quality Management and House Model (Mikušová, 2011). Fourth category i.e. corporate social performance frameworks include Wood’s corporate social performance framework, CSPbroad and CSPnarrow (Pierick et al., 2004) and Aravossis et al. methodological framework.

The systematic review of literature highlights the changing role of businesses in modern capitalist’s societies from a traditional shareholders view to modern social contract within moral and ethical context [1] and stakeholders view [2] (Cooper, 2004). Businesses are not just confronted with challenges restricted to economics (financial and operational) rather these are multifaceted societal and environmental in nature. Therefore, measuring performance of a business organization in 21st century is not simply a function of business’s contribution for the welfare of its shareholder.

To sustain and prosper, firms are required to bridge the economic and social systems by directing their efforts towards maximizing customer delight (Anantharaman, 2007), employee’s welfare (Waal, 2003), social value and environmental protection (WBSD, 2002; O'Rourke 2003) among others. To measure sustainability, the transformation of mindset, commitment of the top leadership and inclusion of key stakeholders in organizational performance measure is necessity (Laszlo, 2003; Waddock and Bodwell, 2007; Sebhatu, 2009). The existing literature (Sethi 1975; Indian National Research Report 2004; Bouquet and Deutsch 2008; Singh et al 2008) looks at CSP as a limited tool to report Corporate Social Responsibilities (CSR) performed by the business. However, recent rethinking of CSP from stakeholder view point (Carroll, 2000; Pierick et al., 2004; Aravossis et al, 2006; Sebhatu, 2009; Wood, 2010) has opened a new vista for CSP measurement literature. Carroll (2000) pointed out that though it is difficult to gather actual measures for measuring CSP, relying on stakeholders’ views can be a more reliable way of measuring corporate social activities compared to alternative methods in the literature (Turker, 2009).#p#分頁(yè)標(biāo)題#e#

The literature review highlighted the need for developing a holistic performance measurement framework which should integrate CSR aspects i.e. environmental and social performance with business economic performance i.e. financial and operational performance (Johnson, 2007; Schaltegger and Wagner, 2006; Epstein and Roy, 2003). Turker, 2009, Taneja et al, 2011, Perrini et al, 2012 suggested that this holistic performance measurement framework for catering the needs of the entire stakeholder community can be developed by implementing stakeholder theory. The first step in the direction of developing a holistic performance measurement framework is to develop scales for measuring CSP on the basis of stakeholders’ perceptions (Turker, 2009). Therefore, the focus research problem for this study was to derive appropriate set of measures to measure CSP and CFP, populate them into a performance measurement matrix, which should be comprehensive enough to incorporate not only economic measures (financial performance + operational performance) but also the social measures.

The theoretical and methodological considerations for measuring corporate economic and social performance by stakeholder approach have been discussed in chapter three of the study. First section of chapter 3 provides a glimpse of the unconcluded quest of four decades ago (Perrini et al., 2012) to investigate the relationship between corporate social performance (CSP) and corporate financial performance (CFP). Other than stakeholder theory the study has been guided by numerous other theories such as agency theory, resource dependence theory, institutional theory and social contract theory. Section two of the chapter sheds light on guiding theoretical grounding to develop holistic performance measurement framework.

The subsequent sections of the chapter shown the path way (i.e. research questions, research methodology and research process) to reach proposed framework of corporate economic social performance by stakeholder approach.

Research questions answered in study include who are the relevant stakeholders, what are their expectations, which expectations of these stakeholders should be considered for constructing valid and reliable scales for measuring social performance of the companies, how to integrate economic performance of the organizations with social performance of the company to determine overall performance of the company and how to evaluate the overall performance of an organization in comparison to other set of organizations.

To answer these research questions an introspective reflection research paradigm with sequential mixed method research design has been used. Both qualitative and quantitative approaches have been adopted to develop the scales for measuring stakeholders’ expectations. To monitor the research progress seven major landmarks have been identified in research process. In first and second stage relevant stakeholders and their expectations have been identified with the help of intensive literature review and conceptual and relational analysis has been carried out. In the third stage to finalize the social performance indicators expectations identified in previous step were converted into statements in a semi-structured questionnaire format.

A total of 85 experts from industry and academia representing each stakeholder category were asked to rate the statements in semi structured questionnaires for their relevance and clarity. In addition to rating in-depth discussions were made with experts to test the face and content validities of the indicators and sub constructs identified as a result of previous stage. In the next stage results of experts’ ratings and comments were analyzed and final tools for data collection were prepared. Eight companies had given permission for data collection from its stakeholders, consisted the sampling framework of the study. These eight companies were a mix of public/private/foreign joint venture/profit/loss making corporations, representative of manufacturing companies in India. Tools were piloted tested at Shreyans Industries Ltd., Plant at Mandi Ahemadhgarh, Punjab, India. Exploratory factor analysis and reliability testing were conducted on the results obtained in pilot testing. Final data was collected from a total sample of 1058 stakeholders with the help of quota sampling.#p#分頁(yè)標(biāo)題#e#

The collected data about stakeholders’ expectations was analyzed by using Confirmatory Factor Analysis (CFA) (Bentler, 1995; Sureshchandar, 2002) for development of standardized scales for CSP measurement. Scales items were tested and retested to satisfy the criterions of uni-dimensionality, reliability and validity (Byrne, 1994) with help of CFA. Finally, to measure the overall performance (i.e. both economic and social performance) of the selected sample companies’, data envelopment analysis with output oriented approach had been used. Operational performance of the companies had been taken as input and financial and social performance had been taken as output measures to calculate overall technical, managerial and scale efficiencies of the companies with variable return to scale model (Banker, Charnes, and Cooper, 1984).

Chapter 4 of the study begins with looking for answer for first research question i.e. identifying the relevant stakeholders for the study. For identification of relevant stakeholders for the study Freeman’s widely accepted (Fassin, 2009) and landmark (Wood, 1991; Clarkson, 1995; Rowley, 1997; Andriof and Waddock, 2002) definition “….any group or individual who can affect or is affected by the achievement of the organization's objectives,” has been used. On the basis of intensive literature review of studies in Western and Indian context (Ramakrishnan, 2012; Fassin, 2009; Prasad and Sri, 2008; Cooper 2004; Post et al., 2002b ; Mohan, 2001; Spence et al., 2001; Clarkson 1995; Freeman 1984) six main stakeholders identified include shareholders, employees, customers, suppliers, communities, and government. Considering the limited time and resources, the scope of the study has been restricted only to four key stakeholders i.e. shareholders, employees, customers and communities similar to Atkinson et al. (1997) and Besser and Jarnagin (2010).

The second section of this chapter focuses on details of qualitative research methodology used for answering second research question i.e. identifying expectations of above identified stakeholders. A multistage qualitative research approach consisting of systematic comprehensive literature review by using ‘citation pearl growing’ method (Hartley, 1990 cited in Dolan et al., 2004), conceptual analysis and relational analysis have been used. To identify the expectations of each relevant stakeholder in the first stage conceptual analysis was carried out on identified literature studies to list various expectations of each stakeholder.

In next stage, items indentified for measuring expectations of each stakeholder category were converted in to statements in structured questionnaires for each category. Experts from respective field in stakeholder category were asked to rate the statements on basis of relevance and clarity. Other than quantitative descriptive analysis on experts rating explained above, a qualitative analysis i.e. relational analysis with help of mental models [3] have been carried out. The main objective of relational analysis was to embed (Creswell and Clark 2007) the quantitative finding through expert rating, comments of the experts and the result of conceptual analysis of literature. Relational analysis helped the researcher to group related concepts and items under sub-constructs for each stakeholder expectation category. Further, it helped to remove some of the items which were conveying the same meaning or not found much citation in manufacturing industry context or suggested by experts.#p#分頁(yè)標(biāo)題#e#

With the help of mental models eight sub-constructs have been drawn from the originally grouped 40 concepts of employees’ expectations (See Figure 4.7). These concentration areas of employees’ expectations are work place environment (Smith et al, 1983; Judge et al., 2002; Egan et al, 2004) organizational support (Eisenberger et al, 1986; Randall et al. 1999; Rhoades and Eisenberger, 2002; Qu et al, 2008); recruitment & selection system (Lado and Wilson, 1994; Neal and Tromley, 1995; Tsai, 2006; Masood, 2010); physiological needs (Salancik and Pfeffer 1977; Miskel and Ogawa, 1988; Oishi et al, 1999) social needs (Friedlander and Margulies 1969; Kalleberg, 1997; Miskel and Ogawa, 1988; Morrison 2005) performance appraisal (Blau, 1999; Judge et al., 2001; Poon, 2004); feedback (Locke, 1976; Williams and Anderson 1991; Judge et al, 2001; O'REILLY and Anderson, 2006) and community care (Knoop, 1994; Turban and Greening 1997; Judge and Bono, 2001; Cooper 2004; Borzaga and Depedri, 2005; Taneja et al. 2011).

Similar to employees’ expectation model, mental model for customers’ expectations grouped 38 concepts in to eight sub-constructs (See Figure 4.8) i.e. customer relationship management (Winer, 2001; Chen and Popovich 2003; Reinartz et al, 2004; Mithas et al., 2005); pricing (Fornell et al., 1996; Hallowell, 1996; Cronin et al, 2000; Homburg et al., 2005); product development (Clark and Fujimoto 1991; Matzler and Hinterhuber, 1998; Kaulio, 1998; Griffin and Page, 2003); promotion (Cardozo,1965; Fornell,1992; Rust and Zahorik,1993; Anderson et al, 1994; Fornell et al., 1996; Luo and Homburg, 2007); product distribution (Cooper, 1979; Bowersox and Morash, 1989; Anderson et al, 1994; Fornell et al., 1996; Beamon, 1998; Athanassopoulos, 2000; Ball et al., 2004); quality assurance (Garvin, 1984; Andreassen and Lindestad 1998; Choi and Eboch, 1998; Cronin et al, 2000; Kettinger and Lee 2007); process (Churchill Jr and Surprenant, 1982; Fornell,1992; Woodruff and Gardial, 1996; Luo and Homburg, 2007) and social responsible behavior (File and Prince, 1998; Sen and Bhattacharya, 2001; D'Souza et al., 2006; Prior et al, 2008).

Community expectations construct has also grouped 40 concepts in to eight sub-constructs (See Figure 4.9) i.e. CSR in action (Galan, 2006; Den Hond, 2007; Lindgreen and Swaen, 2010; Chandler and Werther Jr, 2010; Taneja et al., 2011); good governance (Levi, 1996; Woolcock and Narayan, 2000; Bouckaert and Van de Walle, 2003; E Ite, 2004); triple bottom line (Elkington, 1998; Norman and MacDonald, 2004; Fauzi et al., 2010); corporate communication (Heath, 1994; Gray and Balmer, 1998; Varey and White, 2000; Bruning, 2002; Berrone et al., 2007) socially responsible reporting (Armstrong and Sweeney, 2001; Vuontisjärvi, 2006; Buys et al., 2009; Bhattacharya et al. 2011); sustainable business development (Prahalad and Hart, 2002; Rainey, 2006); sustainable production process (Jeston and Nelis, 2008; D’Amato et al., 2009; Petrini and Pozzebon, 2010) and philanthropy (Seifert et al. 2004; Godfrey, 2005; Hall, 2006; Gardberg and Schepers, 2008).#p#分頁(yè)標(biāo)題#e#

In shareholders expectations construct 50 concepts have been grouped in to six sub-constructs (See Figure 4.10) i.e. corporate governance (Donaldson and Davis, 1991; Cadbury, 1992; Shleifer and Vishny, 1997; Lazonick and O'sullivan, 2000); building core competence (Chase, 1997; Civi, 2000; Luo et al., 2011); core responsibility (Reich, 1998; Waddock, 2003; Hockerts and Moir, 2004; Krizov and Allenby 2004; Fieseler, 2011); financial reporting (Ball and Foster, 1982; Beasley et al., 1999; Kaplan and Norton, 2001; Wiesel, et al, 2008); sustainable development practices (Goldsmith and Samson, 2005; Beheiry et al., 2006; Nejati, et al., 2010); and returns to society (Azapagic, 2004; Richardson, 2009; Maltz et al, 2011).

The chapter 5 of the study focuses on constructing valid and reliable scales for measuring social performance of the companies on the basis of expectations of the stakeholders identified in chapter 4. The first section of this chapter explains the details of the quantitative research methodology used for building scales for measuring expectations of stakeholders. As explained above, for developing and validating measurement items and their associated multi-item scales, a multi-stage approach [4] , has been applied (See Figure 5.2). Quantitative research methodology used for building scales include sub sections on survey instrument design process, criterions for selection of sample companies, criterions for reaching to respondents, sample size, sampling procedure, data collection process and characteristics of sample respondents.

In next section on scale development process, for checking the initial plausibility of the factor structure i.e. testing the relationships between the observed and latent (factors) variables, the developed tools were pilot tested on the stakeholders of one pre-selected company. The results tested with the help of exploratory factor analysis [5] (EFA) i.e. Principal Components Analysis (PCA) by Varimax with Kaiser Normalization have shown that the variance explained and Cronbach alpha values for most of the factors were higher than admissible limit. Few cases where variance explained or Cronbach’s alpha was even less than permissible limits, factor were noted but not ignored at this stage as sample size was very small.

Further in scale development process, after successful pilot testing on finalized tool data was collected from all stakeholders of remaining selected seven companies. The collected data was entered and then re-entered (to avoid non-sampling and typographical errors) in statistical software. To test the normality of data the critical ratios for skewness and kurtosis were found, which were found more than 1.96, therefore, the collected data was statistically normally distributed. Further, on the entered data, an iterative procedure was carried out to satisfy for all requirements of reliability, validity and unidimensionality. In data screening process, scale items with alpha values equal or more than 0.60 were retained. For those scales where alpha is less than 0.60, inter-item correlations were determined and the items with very low inter-item correlations were deleted. To test non-response bias T-tests were performed for the mean value of randomly selected six survey items, of first 15 and last 15 respondents. T-test results indicate no significant difference between the two sets of responses therefore; non-response bias is not a problem with data collected. An exploratory principle component analysis using maximum-likelihood extraction and oblique (varimax) rotation was performed on the data to identify underlying factor structure and get initial uni-dimensionality (Convergent validity) and discriminant validity of the constructs. The results of evaluation of the correlation matrix through the KMO and Bartlett’s test of all constructs indicated that sufficient correlations within the correlation matrix for factor analysis to proceed. Cronbach’s alpha for each construct ranging from 0.845 to 0.951 indicated good reliabilities of the measures.#p#分頁(yè)標(biāo)題#e#

Since the stakeholder expectations model, its item measures and constructs were formulated on the basis of the literature and qualitative research insights to test the measurement and structural model Structural Equation Modeling (SEM) based on analytic theory with maximum likelihood estimate was used (see Section 5.3). Amos 7 software was used to test the proposed model. For the assessment of the fit of the proposed model, fit of overall model and the fit of internal structure were evaluated with help of literature guideline (Bagozzi and Yi, 1988; Bollen, 1989; Brown and Cudeck, 1993; Byrne, 1998; Chou and Bentler, 1995; Joreskog and Sorbom, 1993; Hair et al., 1998). Since data sources for all four constructs (i.e. Employees, Customers, Sharholders and Community Expectations) were different, four first order initial measurement models were constructed. Each construct was tested for content validity, convergent validity, uni-dimensionality by using the Maximum Likelihood (ML) estimation method in CFA.

Scales for local community expectations confirmed the CSR in action (Taneja et al. 2011) and firm-level social actions (Mattingly and Berman, 2006) frameworks asked to perform with social responsiveness (Carroll, 1979) i.e. company should not engage activities which are detrimental to society and should have a dedicated team to for social projects (Hamann, 2003; Porter and Kramer, 2006; Rangan et al., 2012). Balmer and Gray (2000) pointed that company’s communications on social and ethical commitments seen as a component of the firm's corporate identity which ultimately enhance corporate performance (Berrone et al, 2007). Therefore, local community of company expects perfect, factual, regular and relevant communication of companies action especially corporate social projects run for them (Varey and White, 2000; Bruning, 2002; Berrone et al., 2007). In the era of sustainable business development, local community also expects integration of triple bottom line (TBL) considerations in all business practices (i.e. policy, system, procedures and reporting) (Jamali, 2006). Local community expects companies should contribute to the economic and social development by innovating technology, products and services to resolve environmental problems and respect employees' human rights (WBCSD, 2001) & value diversity (Knoepfel, 2001).

Rapid market change, disruptive technologies, and opportunities available to your key talent have forced organizations across the globe to carve competitive advantage through the human factor (Naseem et al. 2011). Researches across sectors have shown business success factors such as employee performance/efficiency (Holbeche and Springett, 2003; Hartere et al. 2002), productivity (Maslach et al, 2001), safety (Kahn, 1990; May et al, 2004), attendance and retention (Holbeche and Springett, 2003; Schaufeli et al, 2006), customer service and satisfaction (Roberts and Davenport, 2002), customer loyalty and retention (Gonrig, 2008), Profitability (Seijts and Crim, 2006; Attridge, 2009) etc. are linked to employee engagement and empowerment. Further, to improve corporate image Backhaus et al. (2002) advised the companies to concentrate their efforts on dimensions of CSP. Allen et al. (2003) also concluded that employees’ perceptions of supportive HR practices such as participation in the decision-making process, growth and development opportunities, and fairness of rewards and recognition consistently positively related to increasing employees’ productivity and efficiency.#p#分頁(yè)標(biāo)題#e#

CSP dimensions for employees, in terms of expectations CFA model found in the study also highlights that employees expect fulfillment of their social needs with transparent recruitment selection system, clear job descriptions and healthy participative work place environment supported by organizational system for their development (Figure 5.4). Fulfillment of expectations of the employees will lead higher job satisfaction, lower employees’ turnover ratio which has been directly linked to rising employee recruitment and training costs, low levels of employee morale, and customers’ perceptions of service quality and lower profitability (Dermody et al., 2004). Conducive work place environment can stimulate the employee to utilize his/her abilities, efforts, experiences and skills. It can support employees to develop commitment with the organization as they see the possibility of accomplishing their desires, needs and future expectations, ultimately lead to healthy relationships between employee and employer (Sikh, 2011).

Meijer and Schuyt (2005) postulated CSP acts as two edge sword. On one side, it motivates customers to buy a product but on the other hand, companies that don’t perform a minimum acceptable level of CSP, can face a boycott for the product from the customers. The developed scales for in customer expectations model found that in CSP, customers expect best CRM practices; quality products as specified by them, at fair price with factual and informative promotional activities (Figure 5.5). Fornel et al. (1996) found the similar findings and concluded that in the modem economy [6] customers expect customization with consistent reliable; quality-driven than value or price-driven products. Therefore, to gain customer satisfaction which will only not enhance CFP (Kelsey and Bond, 2001) but also CSP (Meijer and Schuyt, 2005), efforts for price satisfaction (Matzler, 2007) are not sufficient; customize & quality product, customer relationship management, socially responsible promotion practices are highly important (Matzler and Sauerwein, 2002).

Eccles et al. (2012) in a study on the impact of a corporate culture of sustainability on corporate behavior and performance concluded that companies which have voluntarily embraced a sustainable business culture over many years have significantly outperformed their counterparts over the long-term not only in terms of stock market but also accounting performance. The scale for shareholder expectations has also confirmed the same. Kaplan and Norton, (1992) postulated that market value of a company is a function of the market’s (existing and prospective shareholders) perception of a business’s ability to generate returns today and in the future.

In other words, shareholder value is the summation of firm’s current financial performance and expectations for shareholders for future performance. Scales developed in the study emphasized that in future performance, shareholders expect that company should earn high return on assets for them by adopting ethical, socially responsible and sustainable development practices. The company management should behave like a custodian of not just their resources but also of other stakeholders [7] as management creates value with its many stakeholders. Further, they should work for fulfilling their expectations but also of all other stakeholders for their sustainable development and growth in future . Scales developed by the study are in line with characteristics [8] of future high-performance organizations listed in global study on how to build a high-performance organization by American Management Association (2007).#p#分頁(yè)標(biāo)題#e#

The focus of chapter six is to answer the remaining two research questions i.e. How to integrate economic performance of the organizations with social performance of the company to determine overall performance of the company and how to evaluate the overall performance of an organization in comparison to other set of organizations? Literature on performance measurement termed integration of economic with social performance as the sustainable performance measure (Székely and Knirsch, 2008), when environmental performance has also been considered.

To assess the overall performance of firms [9] , empirical studies on performance measurement had used simple linear aggregations, weighted or non-weighted approaches such as sustainability performance ranking, sustainability surveys, sustainability metrics, sustainability indexes, benchmarking, and accreditation processes (Freeman 2003, Kuosmanen and Kortelainen 2007; Székely and Knirsch, 2008; Chen and Delmas, 2011). These types of approaches seem appropriate only on those cases when the weights to the performance indicators are exogenously given (Bird et al. 2007, Hillman and Keim 2001, Mitchell et al. 1997). But this choice of weights becomes herculean task for the corporate managers who work in diverse competitive environment and facing a variety of stakeholder pressures (Clarkson 1995, Delmas and Toffel 2008; Chen and Delmas, 2011). Furthermore, assessment of CSP and CEP (CFP+COP) together would contain both negative and positive indicators to represent strengths and concerns regarding business practices.

Considering the multiple dimensions of the corporate overall performance (CSP+CEP) construct and limitations of the existing performance aggregation methodologies, Jones (1995), Chen and Delmas (2011) and Belu & Manescu (2013) suggested data envelopment analysis [10] (DEA), a mathematical programming method for evaluating the relative efficiencies of firms (Charnes et al. 1978, Cook and Zhu 2006) that does not require a priori weights to aggregate different CSP and CEP issues. DEA calculates an efficient frontier that represents the best performing entities in a peer group. The DEA (CEP+CSP) score represents the distance of a firm to the efficient frontier. This score further represent the extent to which a firm can reduce its current concerns with its given strengths relative to those of the best performers.

For the purpose of this study, an output oriented approach [11] of Data Envelopment Analysis (DEA) has been used Sub-section one, two and three of the chapter six explains what, why and how aspect of DEA analysis technique used for the study.

Operational performance of the companies was taken as input measure, whereas financial and social performance were taken as output measures to calculate overall technical, managerial and scale efficiencies of the companies with Constant and Variable Return to Scale Models (Banker et al., 1984). In operational performance, for raw material input, material cost ratio (Zheng et al., 1998; Oh and Lööf, 2009), for labor input, employee cost ratio (Zheng et al., 1998; Oh and Lööf, 2009; Mostafa, 2007; Zhu, 2000; Wang, 2010) and for other operating cost (including financing cost) other operational expense ratios (Wang, 2010; Halkos and Tzeremes, 2010; Le and Harvie 2010) have been considered as inputs in the study.

Social performance characterized by the four CSP scores for the perceptions of stakeholders: community, employees, customers, and shareholders expectations on the scale developed in section 5.4. Return on investment [12] cited by most of the studies for evaluating financial performance (Griffin & Mahon, 1997; Waddock & Mahon, 1991, Cooper, 2004; Zhu 2004, Waddock and Graves, 1994) has been taken as an indicator for financial performance. Data for operational and financial performance measures have been taken from the audited annual financial statements of the selected companies for 2010-11 year. During the same time period, for social performance, sample stakeholders of the selected companies were asked to answer how much the company is able to meet their expectations (Stakeholders expectations scales developed in section 5.4) on a seven point Likert scale and mean scores were calculated.#p#分頁(yè)標(biāo)題#e#

On basis of above stated input and outputs DEA results for both Charnes, Cooper, and Rhodes (CCR) model i.e. at constant return to scale (CRS) and Banker, Charnes, Cooper (BCC) model at variable return to scale in the form of technical, managerial and scale efficiencies were obtained. DEA results with CCR model i.e. in terms of technical efficiency highlighted that Godfrey Phillips India Ltd., Maruti Suzuki India Ltd., and Sona Koyo Steering Systems Ltd are best performing companies (See Table 6.7). Nahar Spinning Mills Ltd., though on technical efficiency front seems inefficient but after considering scale of operations with BCC model at variable return to scale its managerial efficiency is 100%. The main source of inefficiency for the company is only due to size of its operations which is also even favorable because company is running at increasing return to scale (IRS). JCT Ltd. is the least performing in both managerial inefficiency and improper utilization of economies of scale resulting in to scale inefficiency, are responsible for poor technical efficiency ratio.

Further, from the respective benchmarks of underperforming firms, performance slacks were calculated to identify performance gaps. These identified performance gap help to determine the future course of actions i.e. future target performance for each indicator for each underperforming firm.

In last section of chapter six, a sensitivity analysis has been carried out by making various alternations to the original model to test the sensitivity (or stability) of obtained results with DEA analyses. Results obtained with help of various model in sensitivity analysis have remained stable helps to conclude that results obtained in the original analysis were valid and consistent.

Outcome Measure

Output Measures

Input Measures

7.1: Framework for Measuring Corporate Economic & Social Performance

Local Community Expectations

Social Performance

Shareholders Expectations

Employees Expectations

Customers Expectations

Corporate communication

CSR in Action

Triple Bottom Line

Sustainable Business Development

Customer Relationship Management

Product Development

Pricing

Quality Assurance

Promotion

Recruitment & Selection System

Organizational Support

Work Place Environment

Social Needs

Core Responsibility

Corporate Governance

Returns to Society

Custodian

Sustainable Development Practices

Scales to measures Social Performance

7.2 Contributions & Implications of this Research

In many ways, this research was inspired by a concern for all stakeholders. The major cause of concern was many stakeholders like local community, employee of the company might have been lost in their significance due to an overriding concern for the shareholder in the management literature throughout the last Century. The economic and social purpose of an organization is to use its wealth and enhance its value of its stakeholders i.e. to co-create value and going beyond just the traditional focus on only shareholders (Clarkson, 1995).#p#分頁(yè)標(biāo)題#e#

Corporate Economic & Social Performance framework (See Figure 7.1) developed in this study provides a means through which an organization can convey their values and beliefs towards any issue (Ittner et al, 2003; Neely, 2005). The outcome score of this framework can be used by individual stakeholders as an information processing shortcut in making decision about a firm (Jones and Murrell, 2001). This given comprehensive framework can be used by organizations to measure their social and economic performance using stakeholder approach. The developed scales for measuring CSP for four key stakeholders viz; shareholders, employees, customers and community (see Figure 7.2) can be used for identifying performance gap. On the basis of gaps identified with help of these scales can be used for making future strategy and plan future course of actions to gain competitive advantage. With the help of DEA and these developed scales, by putting all input and output variables together, one single score of performance can be obtained in comparison to various organizations in one industry or across industries. Overall, this developed framework and measures will help an organization to set goals; develop objectives; take stock of organization's capacity to undertake targeted goals; collaborate with outside agencies, organizations and stakeholders; assign accountability not only for day-to-day affairs but pragmatic accountability, roles and responsibilities and lines of authority; improve work quality by fixing benchmarks; track progress on impact of strategic intervention and reporting outcome & progress to all of relevant stakeholders (Lichiello, 1999; O'Leary, 1995; Richmond, 1998; Pratt, 1998; National Center for Public Productivity, 1997; Frederickson & Frederickson, 2006).

Theoretically, this research has used definition of Moullin (2003) [13] and his clarification (2005b) on stakeholder view of performance measurement. The framework developed in study has asked all key stakeholders how they perceive about their organization and measured performance not just their perceptions, traditional accounting measures has given equal importance. The performance framework developed in study has used set of multi-dimensional measures in order to define and demonstrate the impact of activities for fulfilling the needs of relevant stakeholders (Bourne et al., 2003; Franco-Santos et al., 2007). Inbuilt flexibility in the framework offers researchers and organizations to include more factors or delete some of them to make a strategic framework suitable for their organization/research needs.

The scales developed for measuring stakeholders aspect of performance and CESP framework in this study, have used foundations of institutional, resource dependence, social contract and stakeholder theories to build upon the prominent contributions (Kaplan and Norton (1992) [14] , EFQM framework, Neely et al. (2002) [15] , Pierick et al. (2004) [16] ; Mikušová (2011) [17] ) in the field of performance measurement. The research process used in the study has opened vista for future researchers to build a framework for sustainable performance measurement by adding environmental performance measures into corporate economic and social performance measurement framework (Székely and Knirsch, 2008).#p#分頁(yè)標(biāo)題#e#

7.3 Limitations and Areas for Further Research

This study provides strong support for a Corporate Economic and Social Performance (CESP) Measurement model, but it has limitations incurred by the constraints of a doctoral thesis: lack of resources and time for a more in-depth investigation, and inherent deficiencies in some of the applications. These limitations fall into four categories: performance measurement with stakeholders approach construct, sampling framework related issues, the DEA technique and its quirks, and implementation issues. These limitations of study are basically the areas for immediate further research in this field.

As mentioned earlier, while answering second research question related to identification of relevant stakeholders, other than focus four key stakeholders [18] suppliers and government were also identified. Expectations of both of these stakeholders were neither identified nor taken in to considerations in the present corporate economic and social performance measurement framework due to paucity of time and resources. A future research can be conducted by using similar research process to identify expectations of these stakeholders. Further, corporate economic and social performance measurement framework can be extended to sustainable performance measurement framework by researching indicators (measures) for environmental performance, another area ignored by current study.

The sampling frame of a study establishes the context of the study, although around thirty Indian listed companies were contacted for this study but only eight companies had given the permission to conduct the study in their organizations. The sample companies were listed companies in The Economic Times 500 list, primarily having a manufacturing unit in northern India and having more than 20 years of existence. This sampling framework can be further widened and diversified to test the findings of the first phase by adding stakeholders of companies form non-manufacturing sectors (i.e. service sector, not for profit organizations etc.), companies in different parts of India and world, mix of listed and unlisted companies and mix of period of existence.

DEA is an established powerful non-parametric technique. DEA requires a relatively large number of DMUs in order to have robust discriminating power between performing and underperforming units. A common DEA rule of thumb is to have DMUs at least twice the number of the inputs and outputs in a determined node. Since, we had only eight companies who given the permission to interact with their four key stakeholders, therefore, indicators for operational performance (three into one) and social performance (four into one) were merged to fulfill the above rule. Future research with large number of firms (DMUs) can be considered to overcome this issue.

The last but very important widely debated issue in stakeholder research is assignment weights to a particular stakeholder expectations or higher or lower weight to economic or social performance. DEA has the provision for assignment of weightings to the various factors auto or by user. Different weights will undoubtedly affect the results of the computation. In this present study a conservative approach has been used i.e. DEA technique has asked to allocate weighting itself. DEA has been hailed for not requiring or providing absolute scores, that its strength is in its comparative nature; but a detailed study is required to confirm whether weights are required or not.#p#分頁(yè)標(biāo)題#e#

In addition to above areas, a detailed study is required to analyze the relationship between of constructs of one stakeholder on other or vice-versa. Another interesting area for research could be their conditions under which these constructs impact on each other.